References
- Ahtee, M., Lavonen, J., & Pehkonen, E. (2008). Reasons behind the Finnish success in science and mathematics in PISA tests. Problems of Education in the 21st Century, 6, 18–26.
- Anderson, J. O., Milford, T., & Ross, S. P. (2009). Multilevel modeling with HLM: Taking a second look at PISA. In M. C. Shelley, L. D. Yore, & B. Hand (Eds.), Quality research in literacy and science education (pp. 263–286). Dordrecht: Springer.
- Aparicio, J., Cordero, J. M., & Ortiz, L. (2021). Efficiency analysis with educational data: How to deal with plausible values from international large-scale assessments. Mathematics, 9(13), 1579. https://doi.org/https://doi.org/10.3390/math9131579
- Brühwiler, C., & Blatchford, P. (2011). Effects of class size and adaptive teaching competency on classroom processes and academic outcome. Learning and Instruction, 21(1), 95–108. https://doi.org/https://doi.org/10.1016/j.learninstruc.2009.11.004
- Chen, Q. (2016). A multilevel analysis of Singaporean students’ mathematics performance in PISA 2012. In L. M. Thien, N. A. Razak, J. P. Keeves, & I. G. N. Darmawan (Eds.), What can PISA 2012 data tell us?: Performance and challenges in five participating Southeast Asian countries (pp. 17–33). Sense Publishers.
- Choo, T. L., & Darling-Hammond, L. (2011). Creating effective teachers and leaders in Singapore. In L. Darling-Hammond & R. Rothman (Eds.), Teacher and leader effectiveness in high performing education systems (pp. 33–41). Alliance for Excellent Education.
- Christensen, S. (2015). Healthy competition and unsound comparison: Reforming educational competition in Singapore. Globalisation, Societies and Education, 13(4), 553–573. https://doi.org/https://doi.org/10.1080/14767724.2014.979769
- Darling-Hammond, L. (2009). Steady work: How Finland is building a strong teaching and learning system. Voices in Urban Education, 24, 15–25.
- Deboer, G. E. (2011). The globalization of science education. Journal of Research in Science Teaching, 48(6), 567–591. https://doi.org/https://doi.org/10.1002/tea.20421
- Dong, X., & Hu, J. (2019). An exploration of impact factors influencing students’ reading literacy in Singapore with machine learning approaches. International Journal of English Linguistics, 9(5), 52. https://doi.org/https://doi.org/10.5539/ijel.v9n5p52
- EDUFI. (2020). Finnish education system. https://www.oph.fi/en/education-system
- Field, A. (2018). Discovering statistics using IBM SPSS statistics. Sage.
- Guo, C. J. (2007). Issues in science learning: An international perspective. In S. K. Abell & N. G. Lederman (Eds.), Handbook of research on science education (pp. 227–256). Lawrance Erlbaum Associates.
- Hirschmann, R. (2020). Number of immigrants in Singapore 2005–2019. https://www.statista.com/statistics/698035/singapore-number-ofimmigrants/#:~:text=The immigrant population of Singapore, of the country in 2018
- Hsu, J. C. (2007). Comparing the relationships between mathematics achievement and student characteristics in Canada and Hong Kong through HLM [Unpublished doctoral dissertation]. University of Victoria, Canada.
- Huta, V. (2014). When to use hierarchical linear modeling. The Quantitative Methods for Psychology, 10(1), 13–28. https://doi.org/https://doi.org/10.20982/tqmp.10.1.p013
- Ikeda, M., & García, E. (2014). Grade repetition: A comparative study of academic and non-academic consequences. OECD Journal: Economic Studies, 2013(1), 269–315. https://doi.org/https://doi.org/10.1787/eco_studies-2013-5k3w65mx3hnx
- Jimerson, S. R. (2001). Meta-analysis of grade retention research: Implications for practice in the 21st century. School Psychology Review, 30(3), 420–437. https://doi.org/https://doi.org/10.1080/02796015.2001.12086124
- Kivirauma, J., & Ruoho, K. (2007). Excellence through special education? Lessons from the Finnish school reform. International Review of Education, 53(3), 283–302. https://doi.org/https://doi.org/10.1007/s11159-007-9044-1
- Kotte, D., Lietz, P., & Lopez, M. M. (2005). Factors influencing reading achievement in Germany and Spain: Evidence from PISA 2000. International Education Journal, 6(1), 113–124.
- Krapp, A., & Prenzel, M. (2011). Research on interest in science: Theories, methods, and findings. International Journal of Science Education, 33(1), 27–50. https://doi.org/https://doi.org/10.1080/09500693.2010.518645
- Lau, K. C., & Ho, S. C. E. (2020). Attitudes towards science, teaching practices, and science performance in PISA 2015: Multilevel analysis of the Chinese and western top performers. Research in Science Education. https://doi.org/https://doi.org/10.1007/s11165-020-09954-6
- Lian, K. F. (2016). Multiculturalism in Singapore: Concept and practice. In K. F. Lian (Ed.), Multiculturalism, migration, and the politics of identity in Singapore (pp. 11–29). Springer.
- Linnakylä, P. (2004). Finnish education – reaching high quality and promoting equity. Education Review, 17(2), 35–41.
- Magen-Nagar, N. (2016). The effects of learning strategies on mathematical literacy: A comparison between lower and higher achieving countries. International Journal of Research in Education and Science, 2(2), 306–321. https://doi.org/https://doi.org/10.21890/ijres.77083
- Malaty, G. (2006). What are the reasons behind the success of Finland in PISA? Gazette Des Mathématiciens, 108, 59–66.
- Matteucci, M., & Pillati, M. (2014). The unity of Italy from the point of view of student performances: Evidences from PISA 2009. In F. Crescenzi & S. Mignani (Eds.), Statistical methods and applications from a historical perspective (pp. 303–314). Springer.
- OECD. (2006). Assessing scientific, reading and mathematical literacy: A framework for PISA 2006. OECD Publishing.
- OECD. (2016a). Country note: PISA 2015 high performers: Singapore. https://www.oecd.org/pisa/PISA-2015-singapore.pdf
- OECD. (2016b). PISA 2015 results (volume I): Excellence and equity in education. OECD Publishing.
- OECD. (2016c). PISA 2015 results (volume II): Policies and practices for successful schools. OECD Publishing.
- OECD. (2017a). PISA 2015 assessment and analytical framework: Science, reading, mathematics, financial literacy, and collaborative problem solving, revised edition. OECD Publishing.
- OECD. (2017b). PISA 2015 Technical report. OECD Publishing.
- OECD. (2017c). PISA 2015 results (volume III): Students’ well-being. OECD Publishing.
- Ro, J. (2021). On the matter of teacher quality: Lessons from Singapore. Journal of Curriculum Studies, 53(4), 500–515. https://doi.org/https://doi.org/10.1080/00220272.2020.1808903
- Sahlberg, P. (2011). The professional educator: Lessons from Finland. American Educator, 35(2), 34–38. https://doi.org/https://doi.org/10.12968/htup.2012.14.6.92256
- Sahlberg, P. (2012). A model lesson: Finland shows us what equal opportunity looks like. American Educator, 36(1), 20–28.
- Sahlberg, P. (2013). Teachers as leaders in Finland. Educational Leadership, 71(2), 36–40.
- Sahlberg, P. (2015). Finnish lessons 2.0: What can the world learn from educational change in Finland? Teachers College Press.
- Sarjala, J. (2013). Equality and cooperation: Finland’s path to excellence. American Educator, 37(1), 32–36.
- Schiefele, U., Krapp, A., & Winteler, A. (1992). Interest as a predictor of academic achievement: A meta-analysis of research. In K. A. Renninger, S. Hidi, & A. Krapp (Eds.), The role of interest in learning and development (pp. 183–212). Lawrance Erlbaum Associates, Inc.
- Simola, H. (2005). The Finnish miracle of PISA: Historical and sociological remarks on teaching and teacher education. Comparative Education, 41(4), 455–470. https://doi.org/https://doi.org/10.1080/03050060500317810
- Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417–453. https://doi.org/https://doi.org/10.3102/00346543075003417
- Stewart, V. (2010). Raising teacher quality around the world. Educational Leadership, 68(4), 16–20.
- Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Pearson.
- Tan, J. (2009). Private tutoring in Singapore: Bursting out of the shadows. Journal of Youth Studies (Hong Kong), 12(1), 93–104.
- The World Bank. (2020). Databank: Education statistics. https://databank.worldbank.org/source/education-statistics-%5E-all-indicators
- Waldow, F., Takayama, K., & Sung, Y. K. (2014). Rethinking the pattern of external policy referencing: Media discourses over the ‘Asian Tigers’ PISA success in Australia, Germany, and South Korea. Comparative Education, 50(3), 302–321. https://doi.org/https://doi.org/10.1080/03050068.2013.860704
- Woltman, H., Feldstain, A., MacKay, J. C., & Rocchi, M. (2012). An introduction to hierarchical linear modeling. Tutorials in Quantitative Methods for Psychology, 8(1), 52–69. https://doi.org/https://doi.org/10.20982/tqmp.08.1.p052
- Wu, M. (2005). The role of plausible values in large-scale surveys. Studies in Educational Evaluation, 31(2-3), 114–128. https://doi.org/https://doi.org/10.1016/j.stueduc.2005.05.005
- Yeasmin, N., & Uusiautti, S. (2018). Finland and Singapore, two different top countries of PISA and the challenge of providing equal opportunities to immigrant students. Journal for Critical Education Policy Studies, 16(1), 207–237.